Can #ArtificialIntelligence and #MachineLearning play a vital role in insurance industry?

Let's now understand how AI and ML benefit some of the key processes in this sector.

Pricing: Adopting an AI and ML-based pricing model could result in higher customer satisfaction from more personalised policies and competitive premiums. In addition, ML algorithms also possess much better risk sensitivity, enabling adjustments based on price and customer needs.

Claims processing: Traditionally, claims processing has been a manual-intensive task which involves redundant paperwork, written correspondence, and follow-ups. Since AI and ML are capable of quickly extracting relevant information from a large number of documents, they can help automate and speed up the process. This also helps reduce human errors and improve service quality.

Fraud detection: Superior to traditional predictive models for fraud detection, ML models can tap into both unstructured and semi-structured data such as claims notes and documents to spot and flag anomalies. This way, it can help identify potentially fraudulent claims faster and with higher accuracy.

Customer engagement: Customers today are looking for smarter, personalised, and hassle-free insurance services. AI can elevate the level of customer experience with the help of deep learning and applications such as chatbots. AI chatbots and virtual assistants can provide speedy responses to queries and connect more seamlessly.

As you can see, AI and ML can be leveraged across a range of use cases to better serve customer needs in today's ever-evolving industry landscape. As these technologies mature, we see their scope broadening in future-proofing the insurance industry.

Yet another technology that can complement insurers on their journey to the future is cloud computing. We will go over it in detail in the next blog.

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